Methods, apparatus, computer programs, and non-transitory computer readable storage mediums for processing data from a sensor

ABSTRACT

A method of processing data from a sensor, the method comprising: receiving first data; identifying an object by comparing the received first data with stored second data for a plurality of objects; determining a first processing strategy for one or more portions of the object in third data using the identification of the object, the third data being received from a sensor; and processing the determined one or more portions of the object in the third data using the determined first processing strategy.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is based upon and claims the benefit of priority fromBritish Patent Application Number 1614492.5 filed 25 Aug. 2016, theentire contents of which are incorporated by reference.

FIELD OF THE DISCLOSURE

The present disclosure concerns methods, apparatus, computer programs,and non-transitory computer readable storage mediums for processing datafrom a sensor.

BACKGROUND

A sensor may be used to scan one or more surfaces of an object togenerate data associated with the one or more scanned surfaces. Forexample, an optical sensor (such as a complementary metal oxidesemiconductor (CMOS)) uses light reflected from a surface of an objectto generate image data of the scanned surface. A sensor may generate asignificant quantity of data during operation and this may pose a numberof challenges to the operator of the sensor. In particular, a relativelylarge memory may be required to store the data, a relatively largeinternet bandwidth may be required to upload the data to remote memory(which may be referred to as cloud storage), and relatively highprocessing power may be required to analyse the data.

BRIEF SUMMARY

According to various examples there is provided a method of processingdata from a sensor, the method comprising: receiving first data;identifying an object by comparing the received first data with storedsecond data for a plurality of objects; determining a first processingstrategy for one or more portions of the object in third data using theidentification of the object, the third data being received from asensor; and processing the determined one or more portions of the objectin the third data using the determined first processing strategy.

The method may further comprise controlling the sensor to scan theobject to generate the first data.

The third data may be the same data as the first data.

The method may further comprise controlling a sensor to scan the objectto generate the third data. The third data may be different data to thefirst data.

The first processing strategy may include processing the determined oneor more portions of the object in the third data to generate fourthdata.

The fourth data may be a subset of the third data and may only includedata for the one or more portions of the object.

The fourth data may be in a different format to the third data.

The third data may be point cloud data and the fourth data may begeometry model mesh data.

The first processing strategy may include performing analysis todetermine a parameter associated with the condition of the object.

The parameter may be remaining useful life of the object, or may be usedlife of the object, or may be extent of performance degradation, or maybe part acceptability at new, or may be impact on noise.

Performing analysis may include performing a comparison with scanneddata of the object. The scanned data may be generated prior to use ofthe object.

Performing analysis may include performing a comparison with geometrymodel data of the object.

The first data may be received from a sensor.

The received first data may include barcode data.

The received first data may include image data.

The received first data may include three dimensional geometry data.

The received first data may include radio frequency identification(RFID) code data.

The first data may be received from a user input device.

According to various examples there is provided a computer program that,when read by a computer, causes performance of the method as describedin any of the preceding paragraphs.

According to various examples there is provided a non-transitorycomputer readable storage medium comprising computer readableinstructions that, when read by a computer, cause performance of themethod as described in any of the preceding paragraphs.

According to various examples there is provided apparatus for processingdata from a sensor, the apparatus comprising a controller configured to:receive first data; identify an object by comparing the received firstdata with stored second data for a plurality of objects; determine afirst processing strategy for one or more portions of the object inthird data using the identification of the object, the third data beingreceived from a sensor; and process the determined one or more portionsof the object in the third data using the determined first processingstrategy.

The controller may be configured to control the sensor to scan theobject to generate the first data.

The third data may be the same data as the first data.

The controller may be configured to control a sensor to scan the objectto generate the third data. The third data may be different data to thefirst data.

The first processing strategy may include processing the determined oneor more portions of the object in the third data to generate fourthdata.

The fourth data may be a subset of the third data and may only includedata for the one or more portions of the object.

The fourth data may be in a different format to the third data.

The third data may be point cloud data and the fourth data may begeometry model mesh data.

The first processing strategy may include performing analysis todetermine a parameter associated with the condition of the object.

The parameter may be remaining useful life of the object, or may be usedlife of the object, or may be extent of performance degradation, or maybe part acceptability at new, or may be impact on noise.

Performing analysis may include performing a comparison with scanneddata of the object. The scanned data may be generated prior to use ofthe object.

Performing analysis may include performing a comparison with geometrymodel data of the object.

The controller may be configured to receive the first data from asensor.

The received first data may include barcode data.

The received first data may include image data.

The received first data may include three dimensional geometry data.

The received first data may include radio frequency identification(RFID) code data.

The controller may be configured to receive the first data from a userinput device.

The skilled person will appreciate that except where mutually exclusive,a feature described in relation to any one of the above aspects may beapplied mutatis mutandis to any other aspect. Furthermore except wheremutually exclusive any feature described herein may be applied to anyaspect and/or combined with any other feature described herein.

BRIEF DESCRIPTION OF DRAWINGS

Embodiments will now be described by way of example only, with referenceto the Figures, in which:

FIG. 1 illustrates a schematic diagram of apparatus according to variousexamples;

FIG. 2 illustrates a flow diagram of a method of processing data from asensor according to various examples.

FIG. 3 illustrates a perspective view of an object according to variousexamples; and

FIG. 4 illustrates a perspective view of another object according tovarious examples.

DETAILED DESCRIPTION

In the following description, the terms ‘connected’ and ‘coupled’ meanoperationally connected and coupled. It should be appreciated that theremay be any number of intervening components between the mentionedfeatures, including no intervening components.

FIG. 1 illustrates a schematic diagram of apparatus 10 and an object 11.The apparatus 10 includes a controller 12, a user input device 14, anoutput device 16, a sensor arrangement 18, and machinery 20. In summary,the apparatus 10 is configured to determine the identity of the object11 and then use the determined identity to selectively process scanneddata of the object 11 from one or more sensors. The apparatus 10 mayselectively process the scanned data to determine the condition of theobject 11.

In some examples, the apparatus 10 may be a module. As used herein, thewording ‘module’ refers to a device or apparatus where one or morefeatures are included at a later time and, possibly, by anothermanufacturer or by an end user. For example, where the apparatus 10 is amodule, the apparatus 10 may only include the controller 12, and theremaining features (namely, the user input device 14, the output device16, the sensor arrangement 18, and the machinery 20) may be added byanother manufacturer, or by an end user.

The object 11 may be any article, component, or assembly of components.For example, the object 11 may be an aerospace component or an assemblyof aerospace components. In various examples, the object 11 may be acomponent or an assembly of components of a gas turbine engine. Forexample, the object 11 may include an aerofoil (such as a compressorblade, a turbine blade, or a vane), a rotor, a disk, a bladed disk(which may be referred to as a ‘blisk’), a ring, or a bladed ring (whichmay be referred to as a ‘bling’) of a gas turbine engine.

In other examples, the object 11 may be a component for another powergeneration industry, may be a component for the marine industry, or maybe a component for the nuclear industry. For example, the object 11 maya main shaft of a diesel engine, or a valve in a nuclear power station.

In still further examples, the object 11 may include railway line, asection of road, or may be an article being inspected in a failureinvestigation.

The controller 12, the user input device 14, the output device 16, thesensor arrangement 18, and the machinery 20 may be coupled to oneanother via a wireless link and may consequently comprise transceivercircuitry and one or more antennas. Additionally or alternatively, thecontroller 12, the user input device 14, the output device 16, thesensor arrangement 18, and the machinery 20 may be coupled to oneanother via a wired link and may consequently comprise interfacecircuitry (such as a Universal Serial Bus (USB) socket). It should beappreciated that the controller 12, the user input device 14, the outputdevice 16, the sensor arrangement 18, and the machinery 20 may becoupled to one another via any combination of wired and wireless links.

The controller 12 may comprise any suitable circuitry to causeperformance of the methods described herein and as illustrated in FIG.2. The controller 12 may comprise: control circuitry; and/or processorcircuitry; and/or at least one application specific integrated circuit(ASIC); and/or at least one field programmable gate array (FPGA); and/orsingle or multi-processor architectures; and/or sequential/parallelarchitectures; and/or at least one programmable logic controllers(PLCs); and/or at least one microprocessor; and/or at least onemicrocontroller; and/or a central processing unit (CPU); and/or agraphics processing unit (GPU), to perform the methods.

In various examples, the controller 12 may comprise at least oneprocessor 22 and at least one memory 24. The memory 24 stores a computerprogram 26 comprising computer readable instructions that, when read bythe processor 22, cause performance of the methods described herein, andas illustrated in FIG. 2. The computer program 26 may be software orfirmware, or may be a combination of software and firmware.

The memory 24 also stores data 27 for a plurality of objects. Forexample, the data 27 may be a database for a plurality of components ofa gas turbine engine. The data 27 may include a computer aided design(CAD) geometry model for each of the plurality of objects. The data 27may include two dimensional image data and/or three dimensionalgeometrical data for each of the plurality of objects that was generatedby scanning the plurality of objects prior to their operation (in a gasturbine engine for example). The data 27 may include a code for each ofthe plurality of objects that is associated with barcodes on each of theplurality of objects or matches codes stored on radio frequencyidentification (RFID) electronic circuits on the plurality of objects.

The data 27 may also include information concerning the likelihood ofthe surfaces of each of the plurality of objects sustaining wear and/ordamage during operation of the object over a period of time. The data 27may also include information concerning the likely dimensions of thewear and/or damage features (cracks for example) of the plurality ofobjects. This information may be included within the data 27 during thegeneration of a geometry model for an object. For example, thisinformation may be added by an operator during computer aided design ofa geometry model, or may be added by an operator to a geometry modelthat is generated from scanned data of the object 11. Alternatively oradditionally, this information may be added, or updated, after ageometry model has been generated (for example, the data 27 may bedynamically added or updated by a machine learning algorithm executed bythe controller 12 in response to receiving data from the sensorarrangement 18).

The data 27 may include processing strategies for at least some of theplurality of objects and these are described in greater detail later inthe detailed description.

The processor 22 may be located at the same location as the sensorarrangement 18, or may be located remote from the sensor arrangement 18,or may be distributed between the location of the sensor arrangement 18and a location remote from the sensor arrangement 18. The processor 22may include at least one microprocessor and may comprise a single coreprocessor, may comprise multiple processor cores (such as a dual coreprocessor or a quad core processor), or may comprise a plurality ofprocessors (at least one of which may comprise multiple processorcores).

The memory 24 may be located at the same location as the sensorarrangement 18, or may be located remote from the sensor arrangement 18(the memory 24 may comprise cloud storage for example), or may bedistributed between the location of the sensor arrangement 18 and alocation remote from the sensor arrangement 18. The memory 24 may be anysuitable non-transitory computer readable storage medium, data storagedevice or devices, and may comprise a hard disk and/or solid statememory (such as flash memory). The memory 24 may be permanentnon-removable memory, or may be removable memory (such as a universalserial bus (USB) flash drive or a secure digital card). The memory 24may include: local memory employed during actual execution of thecomputer program; bulk storage; and cache memories which providetemporary storage of at least some computer readable or computer usableprogram code to reduce the number of times code may be retrieved frombulk storage during execution of the code.

The computer program 26 may be stored on a non-transitory computerreadable storage medium 28. The computer program 26 may be transferredfrom the non-transitory computer readable storage medium 26 to thememory 24. The non-transitory computer readable storage medium 28 maybe, for example, a USB flash drive, a secure digital (SD) card, anoptical disc (such as a compact disc (CD), a digital versatile disc(DVD) or a Blu-ray disc). In some examples, the computer program 26 maybe transferred to the memory 24 via a signal 30 (such as a wirelesssignal or a wired signal). The computer program 26 may be received fromcloud storage which may advantageously enable the computer program 26 tobe updated relatively quickly.

Input/output devices may be coupled to the apparatus 10 either directlyor through intervening input/output controllers. Various communicationadaptors may also be coupled to the controller 12 to enable theapparatus 10 to become coupled to other apparatus or remote printers orstorage devices through intervening private or public networks.Non-limiting examples include modems and network adaptors of suchcommunication adaptors.

The user input device 14 may comprise any suitable device for enablingan operator to at least partially control the apparatus 10. For example,the user input device 14 may comprise one or more of a keyboard, akeypad, a touchpad, a touchscreen display, a computer mouse, and anaugmented reality input device. The controller 12 is configured toreceive signals from the user input device 14.

The output device 16 may be any suitable device for conveyinginformation to an operator. For example, the output device 16 mayinclude a display (such as a liquid crystal display (LCD), or a lightemitting diode (LED) display, or an active matrix organic light emittingdiode (AMOLED) display, or a thin film transistor (TFT) display, or acathode ray tube (CRT) display), and/or a loudspeaker, and/or a printer(such as an inkjet printer or a laser printer). The controller 12 isarranged to provide a signal to the output device 16 to cause the outputdevice 16 to convey information to the operator.

The sensor arrangement 18 may include one or more sensors for scanningthe object 11. For example, the one or more sensors may include one ormore co-ordinate measuring machines (CMM) (such as a contact co-ordinatemeasuring machine or a non-contact measuring machine), one or moreoptical sensors (such as one or more charge coupled device (CCD) camerasor one or more complementary metal oxide semiconductor (CMOS) cameras),one or more infra-red sensors, one or more X-ray sensors, one or moreacoustic wave sensors (such as one or more ultrasonic transducers), orradio frequency circuitry (such as a radio frequency identification(RFID) electronic circuits). The one or more sensors may additionallyinclude one or more emitters such as structured light emitters, lasers,X-ray sources, and acoustic wave emitters (such as ultrasonictransducers), and/or a receiver or transceiver of radio frequencyelectromagnetic waves.

In the example illustrated in FIG. 1, the sensor arrangement 18 includesa first sensor 32, a second sensor 34, and a third sensor 36. In variousexamples, the first sensor 32 includes a digital camera (comprising acomplementary metal oxide semiconductor sensor or a charge coupleddevice sensor for example), the second sensor 34 includes one or morelasers and an optical sensor, and the third sensor 36 includes anacoustic wave transducer (such as an ultrasonic transducer).

The controller 12 is configured to control the operation of the sensorarrangement 18. For example, the controller 12 may control a structuredlight emitter of the sensor arrangement 18 to emit structured light forstereophotogrammetry. In some examples, the sensor arrangement 18 mayinclude one or more actuators (such as one or more servomotors) and thecontroller 12 may control the one or more actuators to control theposition and/or orientation of the sensor arrangement 18.

The controller 12 is also configured to receive data from the sensorarrangement 18. For example, the controller 12 may receive twodimensional image data (which may comprise individual images or videoimages), and/or three dimensional point cloud data, polygon mesh data,triangle mesh data, non-uniform rational B-spline (NURBS) surface modeldata, and/or data from an acoustic wave transducer (such as anultrasonic transducer), and/or code data from a receiver of radiofrequency electromagnetic waves (such radio frequency identificationcode data).

The machinery 20 may include any suitable machinery for performing anaction on the object 11. For example, the machinery 20 may include anysuitable machinery for moving the object 11, and/or changing theorientation of the object 11, and/or removing material from the object11, and/or adding material to the object 11, and/or the addition andremoval of a coating to better image the object 11 (for example, a finewhite matt finish powder coating to avoid reflective surfaces). Thecontroller 12 is configured to control the operation of the machinery 20to perform the action on the object 11.

In the example illustrated in FIG. 1, the machinery 20 includes a robot38, a conveyor 40, and repair apparatus 42. The robot 38 may be a ‘pickand place’ robot (such as a robotic arm) that is configured to move theobject 11 over relatively short distances (up to one or two meters forexample) and/or to change the orientation of the object 11. The conveyor40 is configured to move the object 11 over relatively long distances(around a repair facility or around a manufacturing site for example).The repair apparatus 42 may include any apparatus for removing materialfrom the object 11 and/or any apparatus for adding material to theobject 11. For example, the repair apparatus 42 may include one or moremachine tools (such as a blending tool, a grinding tool, a drill),and/or welding apparatus, and/or chemical vapour deposition (CVD)apparatus.

The operation of the apparatus 10 is described in the followingparagraphs with reference to FIGS. 1 to 4.

Initially, the method may include controlling movement of the object 11towards the sensor arrangement 18. For example, the controller 12 maycontrol the robot 38 and/or the conveyor 40 to move the object 11towards the sensor arrangement 18 to enable the sensor arrangement 18 toscan the object 11.

At block 44, the method may include controlling a sensor to scan atleast a part of the object 11 to generate first data. For example, thecontroller 12 may control the first sensor 32 of the sensor arrangement18 to scan at least a part of the object 11 to generate two dimensionalimage data of the object 11.

FIG. 3 illustrates a perspective view of an object 11 ₁. The object 11 ₁is a cube having a first face 46 ₁, a second face 46 ₂, a third face 46₃, a fourth face 46 ₄, a fifth face 46 ₅, and a sixth face 46 ₆. Thefirst face 46 ₁ includes a first feature 47 ₁, the second face 46 ₂includes a second feature 47 ₂, and the fifth face 46 ₅ includes a thirdfeature 47 ₃. The first feature 47 ₁, the second feature 47 ₂ and thethird feature 47 ₃ may be any physical features of the object 11 ₁ andmay be, for example, protrusions, recesses, flanges, apertures.

At block 44, the controller 12 may control the sensor arrangement 18 toscan the first face 46 ₁, the second face 46 ₂ and the fifth face 46 ₅.

FIG. 4 illustrates a perspective view of another object 11 ₂. The object11 ₂ is a cube having a first face 48 ₁, a second face 48 ₂, a thirdface 48 ₃, a fourth face 48 ₄, a fifth face 48 ₅, and a sixth face 48 ₆.The first face 48 ₁ includes a first feature 49 ₁ and the second face 48₂ includes a second feature 49 ₂. The first feature 49 ₁ and the secondfeature 49 ₂ may be any physical features of the object 11 ₁ and may be,for example, protrusions, recesses, flanges, apertures.

The fifth face 48 ₅ includes a barcode 50 that occupies a subset of thearea of the fifth face 48 ₅. The barcode 50 may be a one dimensionalbarcode (which may also be referred to as a linear barcode), or may be atwo dimensional barcode (which may also be referred to as a matrixbarcode and examples include QR codes). At block 44, the controller 12may control the sensor arrangement 18 to scan the barcode 50 on thefifth surface 48 ₅.

In other examples, the fifth face 48 ₅ may include a radio frequencyidentification (RFID) electronic circuit 50 and the sensor arrangement18 may include a corresponding radio frequency identification (RFID)electronic circuit. At block 44, the controller 12 may control the radiofrequency identification device of the sensor arrangement 18 to scan theradio frequency identification device on the object 11.

At block 52, the method includes receiving first data. The first datamay be received from the sensor arrangement 18. For example, thecontroller 12 may receive first data 53 from any one or more of thefirst sensor 32, the second sensor 34 and the third sensor 36 of thesensor arrangement 18. In some examples, the first data may beadditionally or alternatively received from the user input device 14.For example, an operator may use the user input device to enter a knownpart number for the object 11. The controller 12 may store the receivedfirst data 53 in the memory 24.

At block 54, the method includes identifying the object 11 by comparingthe received first data with stored data for a plurality of objects. Forexample, the controller 12 may identify the object 11 by comparing thefirst data received at block 52 with the data 27 stored in the memory 24(which may also be referred to as second data 27).

For example, where the controller 12 receives two dimensional image dataof the object 11 ₁ from the sensor arrangement 18, the controller 12 mayidentify the object 11 ₁ by using an image recognition algorithm on thereceived first data and the two dimensional images within the storedsecond data 27. The image recognition algorithm may use the position anddimensions of the first, second, and third features 47 ₁, 47 ₂, 47 ₃ toassist with the identification of the object 11 ₁ when comparing thereceived first data 53 and the stored second data 27. Where thecontroller 12 determines that the received two dimensional image datamatches an image in the stored second data 27, the controller 12identifies the object 11 ₁ as being the object associated with thematched image in the stored second data 27.

Where the controller 12 receives three dimensional data (such as pointcloud data or polygon mesh data) of the object 11 ₁ from the sensorarrangement 18, the controller 12 may identify the object 11 ₁ bycomparing the received three dimensional data with the three dimensionalgeometry models in the stored second data 27. In particular, thecontroller 12 may compare the geometry of the object 11 ₁ and thepositions of the first, second and third features 47 ₁, 47 ₂, 47 ₃ inthe received first data with the geometry and features in the geometrymodels in the stored second data 27 to identify the object 11 ₁. Wherethe controller 12 determines that the received three dimensional datamatches three dimensional data within the stored second data 27 (withinacceptance limits), the controller 12 identifies the object 11 ₁ asbeing the object associated with the matched geometry model in thestored second data 27.

Where the controller 12 receives a code (such as a barcode or an RFIDcode) in the received first data from the sensor arrangement 18, thecontroller 12 may identify the object 11 ₂ by comparing the receivedcode with the codes within the stored second data 27. Where thecontroller 12 determines that the received code matches a code withinthe stored second data 27, the controller 12 identifies the object 11 ₂as being the object associated with the matched code in the storedsecond data 27.

It should be appreciated that the method may include identifying theobject using multiple different forms of first data. For example, wherethe controller 12 determines that a barcode is not fully legible and isnot able to definitively identify an object, the controller 12 mayadditionally control the sensor arrangement 18 to scan key features ofthe object to identify the object.

At block 56, the method may include controlling one or more sensors toscan the object 11 to generate third data. For example, the controller12 may control the sensor arrangement 18 to scan part of the object 11or the whole of the object 11 to generate third data. The controller 12may also receive the generated third data from the sensor arrangement 18and may store the third data in the memory 24.

In other examples, the method may not include block 56 and the thirddata referred to in the following paragraphs is the same data as thefirst data received at block 52.

At block 58, the method includes determining a first processing strategyfor one or more portions of the object 11 using the identification ofthe object. The one or more portions may be any subset of the identifiedobject 11. For example, the one or more portions may include a pluralityof surfaces of the object (for example, the first, second and fifthfaces 46 ₁, 46 ₂, 46 ₅ of the object 11 ₁), or the one or more portionsmay be only a single surface of an object (for example, the first face46 ₁ of the object 11 ₁), or the one or more portions may be only one ormore subsets of one or more surfaces of an object (for example, thefirst feature 47 ₁ of the first face 46 ₁, and/or the second feature 47₂ of the second face 46 ₂, and/or the third feature 47 ₃ of the fifthface 46 ₅).

The controller 12 may use the identification of an object from block 54to read a processing strategy for that object from the memory 24. Theprocessing strategies may be stored as part of the stored second data27, or may be stored in a separate database that associates each of theplurality of objects with a processing strategy.

Alternatively, the controller 12 may use the identification of an objectto generate a processing strategy using data stored in the memory 24.For example, the controller 12 may use the data for the likelihood ofthe surfaces of an object sustaining wear and/or damage during operationin the stored second data 27 to generate the processing strategy. Wherethe controller 12 determines that a surface has a greater likelihood ofsustaining wear, the controller 12 may generate a processing strategythat results in only that surface being analysed. By way of anotherexample, where the identified object does not have an associatedprocessing strategy, the controller 12 may compare the identified objectwith the plurality of objects in the second data 27. Where theidentified object is similar to one of the objects in the second data27, the controller 12 may use the processing strategy of the similarobject for use with the identified object.

A processing strategy for an object may direct that the object beanalysed in a non-uniform manner by the controller 12. Such a processingstrategy typically results in analysis being performed for areas ofinterest on the object (for example, areas that are likely to havesustained damage or wear during operation) and not for areas of lowerinterest (for example, areas that are less likely to have sustaineddamage or wear during operation).

The first processing strategy may include processing the one or moreportions of the object 11 in the third data to generate fourth data 60.The fourth data 60 may be a subset of the third data and may onlyinclude data for the one or more portions of the object 11. The fourthdata 60 may be in a different format to the third data. For example,where the third data is three dimensional point cloud data for the wholeof the object 11 ₁, the controller 12 may only convert the point clouddata for the first face 46 ₁ into geometry model mesh data 60.

The first processing strategy may include processing third data from twoor more different sensors 18. For example, the first processing strategymay include processing coloured two dimensional image data and threedimensional data. The two or more different types of data may enable thecontroller 12 to more accurately identify the features of an object 11and to determine the dimensions of such features. For example, thecoloured two dimensional image data may be used by the controller 12 toidentify the location of a crack in an object (since the crack may bedarker than the surrounding surface) and the three dimensional data maybe used by the controller 12 to identify the dimensions of the crack.

The first processing strategy may include targeting areas of the object11 within the third data that were previously identified in an earlierscan of the same object, for example, to build a degradation parameterwith time for the object 11.

The first processing strategy includes performing analysis to determineone or more parameters 63 associated with the condition of the object11. In some examples, the controller 12 may perform analysis on only thefourth data 60 to determine one or more parameters 63 associated withthe condition of the object 11. For example, where the fourth data 60 isgeometry model mesh data 60 of the first face 46 ₁, the controller 12may only analyse the features of the first face 46 ₁ (such as the firstfeature 47 ₁) to determine one or more parameters 63 associated with thecondition of the object 11. The one or more parameters 63 associatedwith the condition of the object 11 may be remaining useful life of theobject 11, used life of the object 11, extent of performancedegradation, part acceptability at new, and impact on noise.

In other examples, the controller 12 may perform analysis on only thesubset of the third data that corresponds to the one or more portions ofthe object 11 to determine a parameter 63 associated with the conditionof the object 11. For example, where the third data is three dimensionalmesh data for the whole of the object 11 ₁, the controller 12 may onlyanalyse the first feature 47 ₁ in the three dimensional mesh data todetermine the parameter 63.

At block 64, the method includes processing the determined one or moreportions of the object 11 using the determined first processingstrategy. For example, the controller 12 may use the determined firstprocessing strategy to generate fourth data 60 from the third data, andthe controller 12 may then analyse the fourth data 60 to determine oneor more parameters, such as the remaining useful life of the object 11,and/or the used life of the object 11, and/or extent of performancedegradation, and/or part acceptability at new, and/or impact on noise.

In some examples, an object 11 may be scanned prior to use (immediatelyafter manufacture of the object 11 for example) and the scanned data(which may be a two dimensional image data, or three dimensionalgeometry data) may be stored in the memory 24. The controller 12 maycompare the third data and/or the fourth data 60 with the scanned dataof the object 11 to determine one or more parameters 63 associated withthe condition of the object 11.

In other examples, the controller 12 may compare the third data and/orthe fourth data 60 with the second data 27 stored in the memory 24 todetermine one or more parameters 63 associated with the condition of theobject 11. For example, the controller 12 may compare the third dataand/or the fourth data 60 with a geometry model of the object 11 in thesecond data 27 stored in the memory 24.

At block 66, the method may include controlling performance of an actionusing the determined one or more parameters 63. For example, thecontroller 12 may determine that the condition of the object 11 is belowa first threshold (indicating that the object 11 is not repairable), andmay then control the conveyor 40 to move the object 11 to ascrap/recycling heap. By way of another example, the controller 12 maydetermine that the condition of the object 11 is above the firstthreshold, but below a second threshold (indicating that the object 11is not suitable for use, but is repairable), and may then control theconveyor 40 to move the object 11 to the repair apparatus 42. Once theobject 11 arrives at the repair apparatus 42, the controller 12 maycontrol the repair apparatus 42 to repair the object 11.

The controller 12 may rank the object 11 acceptability forre-use/repair/scrap using a range of parameters including life,performance degradation, impact on noise, and so on. Furthermore, thealgorithm executed by the controller 12 may not be a simple criteria ofsatisfying a threshold of part condition or even a fixed forward lifebut one that can adjust based on a current condition based on existinglife and a forward life need (for example, two thousand hours more dutywould have a different acceptance to four thousand hours more duty). Theoperator may use the user input device 14 to adjust the thresholds forthe actions.

The method may then return to block 44 for the same object, or mayreturn to block 44 for a new object. Alternatively, the method may end.

The apparatus 10 and the methods described above may be advantageous inthat the controller 12 may selectively process data from the sensorarrangement 18 using knowledge of the identity of the object 11. Theselective processing of the data may result in block 64 being performedmore quickly since only a subset of the scanned data is analysed. Thismay enable a higher rate of objects 11 to be processed according to themethod illustrated in FIG. 2. Alternatively, the selective processing ofthe data may enable reduced computing power to be used when compared toa method were selective processing is not used. The apparatus 10 and themethods described above may also be advantageous in that they may enableobjects to be automatically inspected and repaired with little or nohuman intervention.

The apparatus 10 and the methods described above may also beadvantageous in that data may be stored to build a statisticalunderstanding of one or more parameters of the object 11. This mayenable the computer program 26 to be adjusted over time to be moreoptimal (thus, the methodology may be an evolving approach to object 11sentencing).

It will be understood that the invention is not limited to theembodiments above-described and various modifications and improvementscan be made without departing from the concepts described herein. Forexample, the different embodiments may take the form of an entirelyhardware embodiment, an entirely software embodiment, or an embodimentcontaining both hardware and software elements.

Except where mutually exclusive, any of the features may be employedseparately or in combination with any other features and the disclosureextends to and includes all combinations and sub-combinations of one ormore features described herein.

The invention claimed is:
 1. A method of processing data from a sensor,the method comprising: receiving first data; identifying an object bycomparing the received first data with stored second data for aplurality of objects; determining a first processing strategy for one ormore portions of the object in third data using the identification ofthe object, the third data being received from a sensor, the firstprocessing strategy comprising performing an analysis to determine aparameter associated with a condition of the object, wherein determiningthe first processing strategy includes determining the one or moreportions of the object based on a likelihood of surfaces of the one ormore portions of the object sustaining wear, damage, or both relative tosurfaces of other portions of the object; processing the determined oneor more portions of the object in the third data using the determinedfirst processing strategy by analyzing the one or more portions of theobject in the third data to determine the parameter associated with thecondition of the object; and determining whether the condition of theobject is below a threshold indicating that the object is notrepairable.
 2. A method as claimed in claim 1, further comprisingcontrolling the sensor to scan the object to generate the first data. 3.A method as claimed in claim 1, wherein the third data is the same dataas the first data.
 4. A method as claimed in claim 1, further comprisingcontrolling a sensor to scan the object to generate the third data, thethird data being different data to the first data.
 5. A method asclaimed in claim 1, wherein the first processing strategy includesprocessing the determined one or more portions of the object in thethird data to generate fourth data.
 6. A method as claimed in claim 5,wherein the fourth data is a subset of the third data and only includesdata for the one or more portions of the object.
 7. A method as claimedin claim 5, wherein the third data is point cloud data and the fourthdata is geometry model mesh data.
 8. A method as claimed in claim 1,wherein the parameter is remaining useful life of the object, or whereinthe parameter is used life of the object or wherein the parameter isextent of performance degradation, or wherein the parameter is partacceptability at new, or wherein the parameter is impact on noise.
 9. Amethod as claimed in claim 1, wherein performing analysis includesperforming a comparison with scanned data of the object, the scanneddata being generated prior to use of the object.
 10. A method as claimedin claim 1, wherein performing analysis includes performing a comparisonwith geometry model data of the object.
 11. A method as claimed in claim1, wherein the first data is received from a sensor.
 12. A method asclaimed in claim 1, wherein the received first data includes barcodedata, or wherein the received first data includes image data, or whereinthe received first data includes three dimensional geometry data, orwherein the received first data includes radio frequency identification(RFID) code data.
 13. A method as claimed in claim 1, wherein the firstdata is received from a user input device.
 14. A non-transitory computerreadable storage medium comprising computer readable instructions that,when read by a computer, cause performance of the method as claimed inclaim
 1. 15. A method as claimed in claim 1 further comprisingcontrolling a conveyor to move the object to a scrap/recycling heap inresponse to a determination that the condition of the object is belowthe threshold indicating that the object is not repairable.
 16. A methodas claimed in claim 1 further comprising building a statisticalunderstanding of one or more parameters of the object.
 17. Apparatus forprocessing data from a sensor, the apparatus comprising a controllerconfigured to: receive first data; identify an object by comparing thereceived first data with stored second data for a plurality of objects;determine a first processing strategy for one or more portions of theobject in third data using the identification of the object, the thirddata being received from a sensor, the first processing strategycomprising performing an analysis to determine a parameter associatedwith a condition of the object, wherein the controller is configured todetermine the one or more portions of the object based on a likelihoodof surfaces of the one or more portions of the object sustaining wear,damage, or both being greater than other portions of the object; processthe determined one or more portions of the object in the third datausing the determined first processing strategy via an analysis of theone or more portions of the object in the third data to determine theparameter associated with the condition of the object; and determinewhether the object is repairable based on the parameter associated withthe condition of the object.
 18. Apparatus as claimed in claim 17,wherein the first processing strategy includes processing the determinedone or more portions of the object in the third data to generate fourthdata.
 19. Apparatus as claimed in claim 17, wherein performing analysisincludes performing a comparison with scanned data of the object, thescanned data being generated prior to use of the object, or whereinperforming analysis includes performing a comparison with geometry modeldata of the object.